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Analyze Text with Tisane Labs API

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Analyze Text with the Tisane Labs API
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Getting Started

Create a workflow to Analyze Text with the Tisane Labs API. When you configure and deploy the workflow, it will run on Pipedream's servers 24x7 for free.

  1. Configure the Analyze Text action
    1. Connect your Tisane Labs account
    2. Select a Language
    3. Configure Content
    4. Optional- Select a Format
    5. Optional- Configure Disable Spellcheck
    6. Optional- Configure Lowercase Spellcheck Only
    7. Optional- Configure Minimum Generic Frequency
    8. Optional- Configure Subscope
    9. Optional- Configure Abuse
    10. Optional- Configure Sentiment
    11. Optional- Configure Document Sentiment
    12. Optional- Configure Entities
    13. Optional- Configure Topics
    14. Optional- Configure Words
    15. Optional- Configure Fetch Definitions
    16. Optional- Configure Parse
    17. Optional- Configure Deterministic
    18. Optional- Configure Snippets
    19. Optional- Configure Explain
    20. Optional- Select a Feature Standard
    21. Optional- Select a Topic Standard
    22. Optional- Select a Sentiment Analysis Type
  2. Select a trigger to run your workflow on HTTP requests, schedules or app events
  3. Deploy the workflow
  4. Send a test event to validate your setup
  5. Turn on the trigger

Integrations

Analyze Text with Tisane Labs API on New Requests from HTTP / Webhook API
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Analyze Text with Tisane Labs API on New Submission (Instant) from Jotform API
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Analyze Text with Tisane Labs API on New Custom Webhook Events from Stripe API
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Analyze Text with Tisane Labs API on New Scheduled Tasks from Pipedream API
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Details

This is a pre-built, source-available component from Pipedream's GitHub repo. The component is developed by Pipedream and the community, and verified and maintained by Pipedream.

To contribute an update to an existing component or create a new component, create a PR on GitHub. If you're new to Pipedream component development, you can start with quickstarts for trigger span and action development, and then review the component API reference.

Analyze Text on Tisane Labs
Description:Analyze text for language, entities, sentiment, and other insights. [See the documentation](https://docs.tisane.ai/#561264c5-6dbe-4bde-aba3-7defe837989f)
Version:0.0.1
Key:tisane_labs-analyze-text

Code

import tisaneLabs from "../../tisane_labs.app.mjs";

export default {
  key: "tisane_labs-analyze-text",
  name: "Analyze Text",
  description: "Analyze text for language, entities, sentiment, and other insights. [See the documentation](https://docs.tisane.ai/#561264c5-6dbe-4bde-aba3-7defe837989f)",
  version: "0.0.1",
  type: "action",
  props: {
    tisaneLabs,
    language: {
      propDefinition: [
        tisaneLabs,
        "language",
      ],
    },
    content: {
      type: "string",
      label: "Content",
      description: "The content to analyze",
    },
    format: {
      propDefinition: [
        tisaneLabs,
        "format",
      ],
    },
    disableSpellcheck: {
      type: "boolean",
      label: "Disable Spellcheck",
      description: "Determines whether the automatic spellchecking is to be disabled. Default: `false`",
      default: false,
      optional: true,
    },
    lowercaseSpellcheckOnly: {
      type: "boolean",
      label: "Lowercase Spellcheck Only",
      description: "Determines whether the automatic spellchecking is only to be applied to words in lowercase. Default: `false`",
      default: false,
      optional: true,
    },
    minGenericFrequency: {
      type: "integer",
      label: "Minimum Generic Frequency",
      description: "Allows excluding more esoteric terms; The valid values are 0 thru 10.",
      min: 0,
      max: 10,
      optional: true,
    },
    subscope: {
      type: "boolean",
      label: "Subscope",
      description: "Enables sub-scope parsing, for scenarios like hashtag, URL parsing, and obfuscated content (e.g. ihateyou). Default: `false`",
      default: false,
      optional: true,
    },
    abuse: {
      type: "boolean",
      label: "Abuse",
      description: "Output instances of abusive conten. Default: `true`",
      default: true,
      optional: true,
    },
    sentiment: {
      type: "boolean",
      label: "Sentiment",
      description: "Output sentiment-bearing snippets. Default: `true`",
      default: true,
      optional: true,
    },
    documentSentiment: {
      type: "boolean",
      label: "Document Sentiment",
      description: "output document-level sentiment. Default: `false`",
      default: false,
      optional: true,
    },
    entities: {
      type: "boolean",
      label: "Entities",
      description: "Output entities. Default: `true`",
      default: true,
      optional: true,
    },
    topics: {
      type: "boolean",
      label: "Topics",
      description: "Output topics. Default: `true`",
      default: true,
      optional: true,
    },
    words: {
      type: "boolean",
      label: "Words",
      description: "Output the lexical chunks / words for every sentence. Default: `false`",
      default: false,
      optional: true,
    },
    fetchDefinitions: {
      type: "boolean",
      label: "Fetch Definitions",
      description: "Include definitions of the words in the output. Only relevant when the `words` setting is `true`. Default: `false",
      default: false,
      optional: true,
    },
    parses: {
      type: "boolean",
      label: "Parse",
      description: "Output parse forests of phrases",
      optional: true,
    },
    deterministic: {
      type: "boolean",
      label: "Deterministic",
      description: "Whether the n-best senses and n-best parses are to be output in addition to the detected sense. If `true`, only the detected sense will be output. Default: `true`",
      default: true,
      optional: true,
    },
    snippets: {
      type: "boolean",
      label: "Snippets",
      description: "Include the text snippets in the abuse, sentiment, and entities sections. Default: `false`",
      default: false,
      optional: true,
    },
    explain: {
      type: "boolean",
      label: "Explain",
      description: "If `true`, a reasoning for the abuse and sentiment snippets is provided when possible",
      optional: true,
    },
    featureStandard: {
      propDefinition: [
        tisaneLabs,
        "featureStandard",
      ],
    },
    topicStandard: {
      propDefinition: [
        tisaneLabs,
        "topicStandard",
      ],
    },
    sentimentAnalysisType: {
      propDefinition: [
        tisaneLabs,
        "sentimentAnalysisType",
      ],
    },
  },
  async run({ $ }) {
    const response = await this.tisaneLabs.analyzeText({
      data: {
        language: this.language,
        content: this.content,
        settings: {
          format: this.format,
          disable_spellcheck: this.disableSpellcheck,
          lowercase_spellcheck_only: this.lowercaseSpellcheckOnly,
          min_generic_frequency: this.minGenericFrequency,
          subscope: this.subscope,
          abusse: this.abuse,
          sentiment: this.sentiment,
          document_sentiment: this.documentSentiment,
          entities: this.entities,
          topics: this.topics,
          words: this.words,
          fetch_definitions: this.fetchDefinitions,
          parses: this.parses,
          deterministic: this.deterministic,
          snippets: this.snippets,
          explain: this.explain,
          feature_standard: this.featureStandard,
          topic_standard: this.topicStandard,
          sentiment_analysis_type: this.sentimentAnalysisType,
        },
      },
      $,
    });

    if (response) {
      $.export("$summary", "Successfully analyzed text.");
    }

    return response;
  },
};

Configuration

This component may be configured based on the props defined in the component code. Pipedream automatically prompts for input values in the UI and CLI.
LabelPropTypeDescription
Tisane LabstisaneLabsappThis component uses the Tisane Labs app.
LanguagelanguagestringSelect a value from the drop down menu.
Contentcontentstring

The content to analyze

FormatformatstringSelect a value from the drop down menu:{ "label": "Review", "value": "review" }{ "label": "Dialog", "value": "dialog" }{ "label": "Shortpost", "value": "shortpost" }{ "label": "Longform", "value": "longform" }{ "label": "Proofread", "value": "proofread" }{ "label": "Alias", "value": "alias" }{ "label": "Search", "value": "search" }
Disable SpellcheckdisableSpellcheckboolean

Determines whether the automatic spellchecking is to be disabled. Default: false

Lowercase Spellcheck OnlylowercaseSpellcheckOnlyboolean

Determines whether the automatic spellchecking is only to be applied to words in lowercase. Default: false

Minimum Generic FrequencyminGenericFrequencyinteger

Allows excluding more esoteric terms; The valid values are 0 thru 10.

Subscopesubscopeboolean

Enables sub-scope parsing, for scenarios like hashtag, URL parsing, and obfuscated content (e.g. ihateyou). Default: false

Abuseabuseboolean

Output instances of abusive conten. Default: true

Sentimentsentimentboolean

Output sentiment-bearing snippets. Default: true

Document SentimentdocumentSentimentboolean

output document-level sentiment. Default: false

Entitiesentitiesboolean

Output entities. Default: true

Topicstopicsboolean

Output topics. Default: true

Wordswordsboolean

Output the lexical chunks / words for every sentence. Default: false

Fetch DefinitionsfetchDefinitionsboolean

Include definitions of the words in the output. Only relevant when the words setting is true. Default: `false

Parseparsesboolean

Output parse forests of phrases

Deterministicdeterministicboolean

Whether the n-best senses and n-best parses are to be output in addition to the detected sense. If true, only the detected sense will be output. Default: true

Snippetssnippetsboolean

Include the text snippets in the abuse, sentiment, and entities sections. Default: false

Explainexplainboolean

If true, a reasoning for the abuse and sentiment snippets is provided when possible

Feature StandardfeatureStandardstringSelect a value from the drop down menu:{ "label": "Universal Dependencies tags", "value": "ud" }{ "label": "Penn treebank tags", "value": "penn" }{ "label": "Tisane native feature codes", "value": "native" }{ "label": "Tisane native feature descriptions", "value": "description" }
Topic StandardtopicStandardstringSelect a value from the drop down menu:{ "label": "IPTC topic taxonomy code", "value": "iptc_code" }{ "label": "IPTC topic taxonomy description", "value": "iptc_description" }{ "label": "IAB topic taxonomy code", "value": "iab_code" }{ "label": "IAB topic taxonomy description", "value": "iab_description" }{ "label": "Tisane domain description, coming from the family description", "value": "native" }
Sentiment Analysis TypesentimentAnalysisTypestringSelect a value from the drop down menu:{ "label": "Products and Services", "value": "products_and_services" }{ "label": "Entity", "value": "entity" }{ "label": "Creative Content Review", "value": "creative_content_review" }{ "label": "Political Essay", "value": "political_essay" }

Authentication

Tisane Labs uses API keys for authentication. When you connect your Tisane Labs account, Pipedream securely stores the keys so you can easily authenticate to Tisane Labs APIs in both code and no-code steps.

Sign in and copy your API key directly from your dashboard.

About Tisane Labs

Home of cutting edge, explainable AI software that turns unstructured content into meaningful insights.

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